Posted
by
timothy
on Monday October 01, 2012 @03:43AM
from the first-one-to-spot-sasquatch-wins dept.

teleyinex writes "ForestWatchers.net is a citizen project with the goal of making it possible for anyone (locals, volunteers, NGOs, governments, etc), anywhere in the world, to monitor selected patches of forest across the globe, almost in real-time, using a computer connected to the Internet. The project has recently released a first alpha web application (built using the open source crowdsourcing PyBossa framework) where volunteers can participate by classifying satellite images of one area of the Amazon basin."

After clicking a few images, I thought the same thing myself. From the half dozen image sets I clicked on it would probably be better to find the one with the least white/gray shades. In other projects like this I have seen (eg: GalaxyZoo), you are asked to do a job that humans really can do better and faster than computers, but "the most green" should be fairly trivial, the only real issue would be the the size of the image archive but they must be managing that already to be able to put this up.

Not trying to troll here, the AC has a good question and I'm genuinely curious as to why they feel automation isn't an option for this task?

I had a look myself. It does seem a bit daft to ask people to do this. Is it easy to tell how sharp an image is? I could also select the best from a row of tiles. List 10s of rows and get more done , so the slow work UI is holding them back.

I'm inclined to wonder if, perhaps, they feel that there is some PR/exposure value to having humans, ideally a fairly large number of vaguely-environmentally-interested-but-not-overly-clueful ones, exposed to the images.

Based on a quick look at the journals, researchers are already using satellite data to study the area(where possible, apparently wholesale slash-and-burn is easy to see, targeted logging of high-value trees rather trickier); but that sort of research has pretty limited circulation. If you already have a serious interest in how screwed the Amazon is, there are people you can ask; but the profile of the issue isn't that high.

Assuming that an algorithm for efficiently crunching and classifying satellite data for forest health purposes were available, that'd definitely be a worthy addition to the literature; but it would also have a very good chance of dying without a ripple among everyone outside the field. Big, machine classified, datasets are a valuable tool for understanding the world; but they just don't have the affective punch of seeing it.

In the specific case of the Amazon, it doesn't help that forests of that type, for all their lush biodiversity, have the curious quirk of locking an impressive percentage of their biological activity into the dense canopy of assorted foliage above the ground. The soil underneath it is actually pretty ghastly. So, not only do you replace a particularly dynamic ecosystem with a monoculture, a few years of rain will leave you with something that looks like Mars, only soggy. Hurray!

In the Epic of Gilgamesh, there is a description of Gilgamesh going on a long journey from the area we now call Iraq, following the Euphrates to the mountains of Syria to fell a large cedar. A lush forest, filled with large dangerous animals is described. The single cedar he floats back to Iraq is large enough to construct the entire city gate of Ur.

Those cedars are long gone, all felled by the hands of man, and what remains is exactly what you describe--a wasteland that we now call The Levant. What remains

This project is a diversion from the logging practices in my own country (US).

"Foresters" in my home state of Washington leave thin strips of trees along highways to hide the clear-cuts from the public. If you fly over these areas, they look like farms--entire regions stripped down to mineral soil as if ready for the Spring planting season. Massive landslides dot the landscape, most of them terminating in a salmon spawning waterway. I live near the site of the largest shingle plant ever built (in the world)

Crowd-sourced "given enough eyeballs all bugs are shallow" NGO's can accomplish far better oversight than government regulators, far more efficiently, with no dangerous concentration of power, abuses, or corruption.

Given that they have no power, they would tend to be in rather limited danger of concentration and/or abuse of power, and are unlikely to be worth the trouble of corrupting. All they'll get to do is watch the forest burn with unprecedented ease and accuracy unless they have somebody else handling the power for them; but they sure are safe...

Poking around at the contributions that users are expected to submit, this seems like a job that Watson or even a simpler machine could be taught to do without much human intervention. One could easily write an algorithm that chooses the most colorful image in the list of candidates. All I found myself doing was looking at a bunch of white cloudy images next to a couple greener images and an occasional black image. It's quite easy to use some color analysis to eliminate ultra-white and ultra-black images

Wouldn't automated infrared monitoring be more effective? You could spot vehicles and brush fires and whatnot pretty easily. Perhaps the problem is that the satellite(s) do not have infrared capabilities.